CN107947201B - Method for judging stability of small disturbance of electric power system caused by wind power fluctuation - Google Patents
Method for judging stability of small disturbance of electric power system caused by wind power fluctuation Download PDFInfo
- Publication number
- CN107947201B CN107947201B CN201711321780.XA CN201711321780A CN107947201B CN 107947201 B CN107947201 B CN 107947201B CN 201711321780 A CN201711321780 A CN 201711321780A CN 107947201 B CN107947201 B CN 107947201B
- Authority
- CN
- China
- Prior art keywords
- wind power
- probability distribution
- key
- real part
- distribution function
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 21
- 238000005315 distribution function Methods 0.000 claims abstract description 38
- 230000010355 oscillation Effects 0.000 claims abstract description 14
- 230000008859 change Effects 0.000 claims abstract description 12
- 238000004458 analytical method Methods 0.000 claims abstract description 8
- 238000004088 simulation Methods 0.000 claims abstract description 6
- 230000001052 transient effect Effects 0.000 claims abstract description 6
- 238000010586 diagram Methods 0.000 claims description 9
- 238000004364 calculation method Methods 0.000 claims description 8
- 230000035945 sensitivity Effects 0.000 claims description 3
- 238000006243 chemical reaction Methods 0.000 claims description 2
- 238000011161 development Methods 0.000 abstract description 2
- 230000007774 longterm Effects 0.000 abstract 1
- 238000010248 power generation Methods 0.000 description 3
- 239000011159 matrix material Substances 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013016 damping Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
-
- H02J3/386—
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/76—Power conversion electric or electronic aspects
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Supply And Distribution Of Alternating Current (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Wind Motors (AREA)
Abstract
The invention discloses a method for judging the stability of small disturbance of an electric power system caused by wind power fluctuation, which comprises the following steps of 1: establishing a wind frequency distribution function of a wind power plant; step 2: establishing power output probability distribution of the wind power plant according to the wind frequency distribution function of the wind power plant obtained in the step 1; and step 3: calculating to obtain a small-disturbance key oscillation mode and a key characteristic root of the power system by adopting an electromechanical transient simulation analysis method; and 4, step 4: based on the key feature root obtained in the step 3, expanding the key feature root in series to obtain a randomly changed probability distribution function of a real part of the key feature root; and 5: and (4) drawing a characteristic value real part probability distribution map based on the probability distribution function of the random change of the real part of the key characteristic root obtained in the step (4), and judging the small disturbance stability characteristic of the power system according to the characteristic value real part probability distribution map, so that the method has good adaptability to long-term development of the power system.
Description
Technical Field
The invention relates to the field of electric power system stability research, in particular to a method for judging the stability of small disturbance of an electric power system caused by wind power fluctuation.
Background
With the continuous forward development of the electric power industry in China, more and more wind power stations are connected to an electric power system. The power generation characteristics of the wind power station are greatly different from those of traditional water conservancy and thermal power generation, mainly in the aspects of randomness and fluctuation of wind power output, the power generation characteristics of wind power have profound influence on the stability of a power system, especially in the direction of small disturbance stability of the power system, the fluctuation of wind power of a wind power station influences the stability characteristics, and more attention is necessary to be paid to the method, and a reasonable system small disturbance stability judgment method is strengthened and researched.
At present, small disturbance factors of an electric power system are mostly considered such as line short circuit faults, sudden push-out operation of electric power equipment and the like, a deterministic characteristic root analysis and calculation method is adopted to analyze the small disturbance stability characteristics of the system, factors of uncertain disturbance such as wind power fluctuation are considered less, and a method for quantitatively calculating the small disturbance stability of the system by adopting a probability analysis method and judging the small disturbance stability of the system does not have a unified standard.
Disclosure of Invention
The invention provides a method for judging the small disturbance stability of an electric power system caused by wind power fluctuation, which solves the problem that the fluctuation characteristic of wind power output cannot be effectively considered in the existing characteristic root analysis and calculation method.
The invention is realized by the following technical scheme:
a method for judging the stability of small disturbance of an electric power system caused by wind power fluctuation comprises the following steps:
step 1: establishing a wind power distribution function of the wind power plant by using historical wind speed data of the wind power plant;
step 2: establishing power output probability distribution of the wind power plant according to the wind frequency distribution function of the wind power plant obtained in the step 1;
and step 3: calculating to obtain a small-disturbance key oscillation mode and a key characteristic root of the power system by adopting an electromechanical transient simulation analysis method;
and 4, step 4: based on the key feature root obtained in the step 3, adopting Gram-Charlier series to expand the key feature root to obtain a randomly changed probability distribution function of the real part of the key feature root;
and 5: and (4) drawing a characteristic value real part probability distribution diagram based on the probability distribution function of the random change of the real part of the key characteristic root obtained in the step (4), and judging the small disturbance stability characteristic of the power system according to the characteristic value real part probability distribution diagram.
The method includes the steps that a probability distribution function of output power of the wind power plant is obtained through actually measuring historical wind power plant data, and randomness and volatility characteristics of wind power are used as a factor influencing small disturbance stability of a power system; the probability distribution function of the random change of the real part of the key characteristic root is obtained by adopting a probability method, the probability distribution diagram of the real part of the characteristic value is drawn according to the function, and the small disturbance stability characteristic of the system is judged.
Specifically, the wind power field wind frequency distribution function in step 1 is: the probability density function PDF of wind power plant wind speed and the probability distribution function CDF of wind power plant output power.
Specifically, the wind power output distribution of the wind farm is obtained through conversion based on the obtained wind power distribution function of the wind farm, and specifically includes: and (4) a probability distribution function CDF of the output power of the wind power plant, so as to establish the power output probability distribution of the wind power plant.
Specifically, the step 3 adopts an electromechanical transient simulation analysis method, and the calculation of the key oscillation mode of the small disturbance of the power system includes: and calculating the key characteristic value of the small disturbance of the power grid and the oscillation frequency corresponding to the key characteristic value.
Specifically, the step 4 includes the following steps:
step 41: firstly, calculating the sensitivity of the characteristic value under the key oscillation mode to the power change, wherein the formula is as follows (1):
wherein P is the power of the wind power plant;
step 42: and (3) constructing a randomly changed probability distribution function of the real part of the key characteristic root under the small disturbance of the power grid by utilizing Gram-Charlier series expansion, wherein the formula is shown as (2):
wherein λ is0Determining a value for the calculation of the real part of the feature root; Δ μ, σ are the mean and variance, respectively, of the random variance of the feature root.
Specifically, according to the probability distribution function of the random change of the real part of the key characteristic root, a characteristic value real part probability distribution graph is drawn, and when F is judged according to judgmentλ(x) When x is less than 0 when the value is 1, judging that the small disturbance of the system is stable; and if x is greater than or equal to 0, judging that the small disturbance of the system is unstable.
Compared with the prior art, the invention has the following advantages and beneficial effects:
the invention relates to a method for judging the small disturbance stability of an electric power system caused by wind power fluctuation, which is characterized in that the probability distribution function of the output power of a wind power plant is calculated by actually measuring historical wind power plant data, and the randomness and the volatility characteristic of the wind power are taken as a factor influencing the small disturbance stability of the electric power system; the probability distribution function of the random change of the real part of the key characteristic root is obtained by adopting a probability method, the probability distribution diagram of the real part of the characteristic value is drawn according to the function, and the small disturbance stability characteristic of the system is judged. .
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a wind frequency distribution characteristic curve of two wind power plants based on historical wind measurement data;
FIG. 3 is a probability distribution plot of a wind farm output power function;
FIG. 4 is a probability distribution diagram of a real part of a key characteristic value of small disturbance of a power system.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following examples, and the exemplary embodiments and descriptions thereof are only used for explaining the present invention and are not to be construed as limiting the present invention.
Examples
As shown in fig. 1 to 4, the method for determining the stability of the small disturbance of the power system caused by the wind power fluctuation of the present invention includes the following steps:
step 1: according to historical wind measuring data of the wind power plant, a wind power plant wind frequency distribution function subject to Weibull distribution is established, and the method comprises the following steps: the probability density function PDF of the wind speed of the wind power plant and the probability distribution function of the output power of the wind power plant are specifically shown as follows:
wherein c is a scale parameter and reflects the average wind speed; k is a shape parameter and reflects the Weibull function shape corresponding to the wind frequency distribution;
step 2: based on the wind power distribution function of the wind power plant obtained in the step 1, converting the wind power distribution function according to the formula (3) to obtain wind power output distribution of the wind power plant, which specifically comprises the following steps: a probability distribution function CDF of the wind farm output power,
in the formula, k0＝(σ/μ)-1.086,k1＝Pr/(Vr-Vc),k2＝-k1Vc，c0＝μ/(1+1/k0) Wherein σ is the anemometric indicator difference; μ is the mean wind speed; () Is a gamma function; pwOutputting active power of the fan; prRated wind power; vcTo cut into the wind speed; vrCutting out the wind speed;
and step 3: the method for determining the small disturbance oscillation characteristics of the power grid by utilizing an electromechanical transient simulation calculation method comprises the following steps: calculating a key characteristic value of the small disturbance of the power grid and an oscillation frequency corresponding to the key characteristic value, wherein the dynamic characteristic of the system can be represented by a differential matrix equation, and a key oscillation mode and a key characteristic root of the small disturbance of the power system are shown as a formula (4):
TABLE 1 Key oscillation modes for small perturbations
| Characteristic value | Frequency of oscillation | Damping ratio of attenuation |
| -0.25477+j3.76175 | 0.5987Hz | 6.757％ |
Solving the above formula to obtain a small disturbance key characteristic value, as shown in the following formula:
wherein the parameters a, b and c are constant terms in a differential matrix equation;
and 4, step 4: and (4) solving a partial derivative of the sensitivity of the key characteristic value obtained in the step (3) to the power change, wherein the partial derivative is shown as a formula (6):
wherein P is the power of the wind power plant;
then, a probability theory developed by a Gram-Charlier series is utilized to construct a probability distribution function of random variation of a real part of a key characteristic root under small disturbance of a power grid, wherein the probability distribution function is shown as a formula (7):
wherein,
the method comprises the following steps of (1) taking a standardized form of random variation of a root real part of a key feature; phi (x) is the probability distribution of the standard normal distribution; g0,1,2Is each coefficient; and (3) obtaining a randomly changed probability distribution function of the real part of the key feature root of the small disturbance of the system through probability transformation, wherein the formula (8) is as follows:
wherein λ is0Determining a value for the calculation of the real part of the feature root; delta mu and sigma are respectively the mean value and the variance of the random variation of the characteristic root;
and 5: drawing a probability distribution diagram of the real part of the characteristic value according to the probability distribution function of the random change of the real part of the key characteristic root obtained in the step 4, and judging when F is reachedλ(x) When x is less than 0 when the value is 1, judging that the small disturbance of the system is stable; and if x is greater than or equal to 0, judging that the small disturbance of the system is unstable.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (2)
1. A method for judging the stability of small disturbance of an electric power system caused by wind power fluctuation is characterized by comprising the following steps:
step 1: establishing a wind power distribution function of the wind power plant by using historical wind speed data of the wind power plant;
step 2: establishing power output probability distribution of the wind power plant according to the wind frequency distribution function of the wind power plant obtained in the step 1;
and step 3: calculating to obtain a small-disturbance key oscillation mode and a key characteristic root of the power system by adopting an electromechanical transient simulation analysis method;
and 4, step 4: based on the key feature root obtained in the step 3, adopting Gram-Charlier series to expand the key feature root to obtain a randomly changed probability distribution function of the real part of the key feature root;
and 5: drawing a characteristic value real part probability distribution diagram based on the probability distribution function of the random change of the real part of the key characteristic root obtained in the step 4, and judging the small disturbance stability characteristic of the power system according to the characteristic value real part probability distribution diagram;
the wind power distribution function of the wind power field in the step 1 is as follows: a probability density function PDF of wind power plant wind speed and a probability distribution function CDF of wind power plant output power;
in the step 3, an electromechanical transient simulation analysis method is adopted, and the calculation of the small disturbance key oscillation mode of the power system comprises the following steps: calculating a key characteristic value of the small disturbance of the power grid and an oscillation frequency corresponding to the key characteristic value;
the step 4 comprises the following steps:
step 41: firstly, calculating the sensitivity of the characteristic value under the key oscillation mode to the power change, as shown in formula (6):
wherein, PwOutputting active power of the fan, wherein lambda is a small disturbance key characteristic value;
step 42: and (3) constructing a randomly changed probability distribution function of the real part of the key characteristic root under the small disturbance of the power grid by utilizing Gram-Charlier series expansion, wherein the formula is shown as (8):
wherein λ is0Determining a value for the calculation of the real part of the feature root; Δ μ, σ are mean and variance of random variation of the feature root, respectively, Fλ(x)A probability distribution function representing the random change of the real part of the key characteristic root under the small disturbance of the power grid,
the method comprises the following steps of (1) taking a standardized form of random variation of a root real part of a key feature;
according to the probability distribution function of the random change of the real part of the key characteristic root, drawing a probability distribution diagram of the real part of the characteristic value, and when F isλ(x) When x is less than 0 when the value is 1, judging that the small disturbance of the system is stable; and if x is greater than or equal to 0, judging that the small disturbance of the system is unstable.
2. The method for judging the stability of the small disturbance of the electric power system caused by the wind power fluctuation according to claim 1, wherein the wind power output distribution of the wind power plant is obtained by conversion based on the obtained wind power distribution function of the wind power plant, and specifically comprises the following steps: and (4) a probability distribution function CDF of the output power of the wind power plant, so as to establish the power output probability distribution of the wind power plant.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711321780.XA CN107947201B (en) | 2017-12-12 | 2017-12-12 | Method for judging stability of small disturbance of electric power system caused by wind power fluctuation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711321780.XA CN107947201B (en) | 2017-12-12 | 2017-12-12 | Method for judging stability of small disturbance of electric power system caused by wind power fluctuation |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107947201A CN107947201A (en) | 2018-04-20 |
| CN107947201B true CN107947201B (en) | 2020-08-11 |
Family
ID=61942849
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711321780.XA Active CN107947201B (en) | 2017-12-12 | 2017-12-12 | Method for judging stability of small disturbance of electric power system caused by wind power fluctuation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107947201B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108616125A (en) * | 2018-05-16 | 2018-10-02 | 天津大学 | Contain asynchronous wind power plant Study of Power System Small Disturbance Method of Stability Analysis based on security domain |
| CN113708384B (en) * | 2021-03-15 | 2023-10-27 | 北京建筑大学 | Wind power network access damping control method and device based on state feedback decoupling control |
| CN113034002B (en) * | 2021-03-26 | 2023-05-23 | 国网江苏省电力有限公司电力科学研究院 | Method for analyzing stability of geomagnetic storm to small disturbance voltage of power system |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102130454B (en) * | 2011-01-26 | 2014-03-12 | 广东电网公司电力科学研究院 | Dynamic stability control method and system for computer aided design based power system |
| EP2927700B1 (en) * | 2014-04-01 | 2019-08-07 | ABB Schweiz AG | Method for monitoring system variables of a distribution or transmission grid |
| CN103915839B (en) * | 2014-04-08 | 2017-01-11 | 华北电力大学 | Method for analyzing stochastic stability of electric power system containing wind electricity |
| CN106709641A (en) * | 2016-12-20 | 2017-05-24 | 南京南瑞继保电气有限公司 | Monte-Carlo simulation based small interference probability risk analysis and simulation method |
-
2017
- 2017-12-12 CN CN201711321780.XA patent/CN107947201B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN107947201A (en) | 2018-04-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Olauson et al. | Modelling the Swedish wind power production using MERRA reanalysis data | |
| CN104319807B (en) | Method for obtaining multi-wind-farm-capacity credibility based on Copula function | |
| CN107947201B (en) | Method for judging stability of small disturbance of electric power system caused by wind power fluctuation | |
| CN106548256B (en) | Method and system for modeling time-space dynamic correlation of wind power plant | |
| CN108695862B (en) | Power grid inertia characteristic online evaluation method based on PMU measured data | |
| Jin et al. | Method for assessing grid frequency deviation due to wind power fluctuation based on “time-frequency transformation” | |
| CN112685939A (en) | Offshore wind turbine foundation fatigue damage analysis method based on actual measurement | |
| CN106786608B (en) | A kind of uncertain harmonic flow calculation method suitable for distributed generation resource access | |
| Nemes et al. | The wind energy system performance overview: capacity factor vs. technical efficiency | |
| CN102709908A (en) | Network loss prediction method after large-scale wind power is connected into power grid | |
| CN113937793B (en) | Stability analysis method based on zero point identification of impedance segmentation reduced order model | |
| CN107657116B (en) | Method for affine modeling of power curve of wind power plant | |
| CN110674864A (en) | Wind power abnormal data identification method with synchronous phasor measurement device | |
| CN107239856A (en) | A kind of wind direction data interpolating method | |
| Al‐Quraan et al. | Power curve modelling of wind turbines‐A comparison study | |
| CN113392365A (en) | High-resolution meteorological grid data generation method and system | |
| Wang et al. | Analysis of wind farm output characteristics based on descriptive statistical analysis and envelope domain | |
| CN104951654A (en) | Method for evaluating reliability of large-scale wind power plant based on control variable sampling | |
| CN103996072B (en) | The wind power forecasting method in a kind of wind energy turbine set and wind-powered electricity generation region and system | |
| Louassa et al. | Effects of local ambient air temperatures on wind park performance: case of the Kaberten wind park | |
| CN105262146A (en) | Method and system for calculating reserve capacity of power system containing wind power | |
| Khahro et al. | Assessment of wind power potential at Hawksbay, Karachi Sindh, Pakistan | |
| CN107221933B (en) | Probabilistic load flow calculation method | |
| CN111756039B (en) | New energy power system inertia estimation method based on probability statistics | |
| CN106251238B (en) | Wind power plant modeling sequence discretization step length selection and model error analysis method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |